Experiment gameplan

Text

Text: Experiment gameplan
  1. Use GffRead to filter Trinity-derived GMAP-aligned gff3 files.
  2. Use featureCounts htseq-count to perform feature counting with respect to types “locus”, “mRNA”, “exon”, and “CDS” features from “base” calls to GffRead, and with respect to type “gene” from “intron-filtering-only” calls to GffRead.
  3. Read in resulting counts matrices and gtf files using custom R code; perform processing as necessary using a mix of bioconductor and tidyverse programs.
  4. In terms of raw, non-normalized alignment-to-putative transcript/transcript fragment (transfrag) tallies, retain putative transcripts/transfrags with tallies greater than or equal to a given percentile; in this case, generate results for the 5th to 95th percentiles in iterations of five.
  5. Use rtracklayer custom code to write the converted, collapsed, counts-filtered data objects as gtf files.
  6. Send the processed gtf files to Alison Greenlaw for inspection.
For both Q and G1, Alison asked me to filter the assemblies generated with Trinity parameter mkc = 1, 4, 8. However, for the sake of completeness, and to understand clearly what “incorrectness” looks like, I will filter mkc = 2, 16, 32 as well. Remember that the Trinity parameters mir, mg, and gf were held at default levels for the specific assemblies to surveyed by Alison.



Additional details

Text, code

Text, code: Additional details

I. On calling gffread

#!/bin/bash

#  "Base" call to GffRead
gffread \
    -v \
    -g "${fasta_g}" \
    -i 1000 \
    -Z \
    -M -K -Q \
    -F -N -P \
    --force-exons --gene2exon \
    -o "${out}" \
    <(awk -F '\t' 'BEGIN {OFS = FS} { gsub(/chr/, "", $1); gsub(/M/, "Mito", $1); print }' "${in}") \
         > >(tee -a "${err_out%.}.stdout.txt") \
        2> >(tee -a "${err_out%.}.stderr.txt")

#  "Intron-filtering-only" call to GffRead
#+ 
#+ No collapsing, merging with these files; only filtering to exclude exonic
#+ features with introns greater than 1000 bp in length
gffread \
    -v -O \
    -i 1000 \
    -o "${out/.gff3/-intron-filtering-only.gff3}" \
    <(awk -F '\t' 'BEGIN {OFS = FS} { gsub(/chr/, "", $1); gsub(/M/, "Mito", $1); print }' "${in}") \
         > >(tee -a "${err_out%.}-intron-filtering-only.stdout.txt") \
        2> >(tee -a "${err_out%.}-intron-filtering-only.stderr.txt")
Meaning of parameters
“Base” call to GffRead
  • -v expose (warn about) duplicate transcript IDs and other potential problems with the given GFF/GTF records
  • -g full path to a fasta file with the genomic sequences for all input mappings (one per genomic sequence, with file names matching sequence names) (#NOTE i.e., the fasta - file output from running Trinity in genome-guided mode)
  • -i discard transcripts having an intron larger than 1000 bp
  • -Z merge very close exons into a single exon (when intron size<4)
  • -M cluster the input transcripts into loci, discarding “redundant” transcripts (those with the same exact introns and fully contained or equal boundaries)
  • -K for the -M option, also discard as redundant the shorter, fully contained transcripts (intron chains matching a part of the container)
  • -Q for the -M option, no longer require boundary containment when assessing redundancy (can be combined with -K); only introns have to match for multi-exon transcripts, and >=80% overlap for single-exon transcripts
  • -F keep all GFF attributes (for non-exon features)
  • -N discard multi-exon mRNAs that have any intron with a non-canonical splice site consensus (i.e., not GT-AG, GC-AG or AT-AC)
  • -P add transcript level GFF attributes about the coding status of each transcript, including partialness or in-frame stop codons (requires -g)
  • --force-exons make sure that the lowest level GFF features are considered “exon” features (#NOTE This is standard in gff3 and gtf files)
  • -o write the output records into instead of stdout
“Intron-filtering-only” call to GffRead
  • -v expose (warn about) duplicate transcript IDs and other potential problems with the given GFF/GTF records
  • -O process other non-transcript GFF records (by default non-transcript records are ignored) (#NOTE This keeps ‘gene’ features (output by gmap) in the gff3/gtf, although “gene” is exactly the same as “mRNA” as output by gmap)
  • -i discard transcripts having an intron larger than 1000 bp
  • -o write the output records into instead of stdout

II. On calling htseq-count

…with respect to type “locus”

As a result of calling gffread with the -Z -M -K and -Q arguments, a new feature is added to the gff3/gtf files: “locus”. “locus” is a putative parent feature made from collapsing and joining “children” features (hierarchically, “mRNA” and “exon”) as described for -Z -M -K and -Q. This is an extension of the kind of collapsing performed by gffcompare -C. Thus, counts matrices were created with respect to these “locus” features.

#!/bin/bash

sbatch \
    --job-name="htseq-count-locus" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-locus.%A.stderr.txt" \
    --output="${err_out}-locus.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "locus" \
        --idattr "ID" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-locus.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
…with respect to type “mRNA”

Create the counts matrix by looking at children “mRNA” features rather than parent “locus” features. This is the kind of collapsing performed by gffcompare -C.

#!/bin/bash

sbatch \
    --job-name="htseq-count-mRNA" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-mRNA.%A.stderr.txt" \
    --output="${err_out}-mRNA.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "mRNA" \
        --idattr "ID" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-mRNA.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
…with respect to type “exon”

Create the counts matrix by looking at children “exon” features.

#!/bin/bash

sbatch \
    --job-name="htseq-count-exon" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-exon.%A.stderr.txt" \
    --output="${err_out}-exon.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "exon" \
        --idattr "Parent" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-exon.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
…with respect to type “CDS”

gffread scans the fastas supplied -g and roughly estimates start and stop codons from the nt sequences; it then adds these CDS estimates to the gff3/gtf files. Create the counts matrix by looking at these estimated “CDS” features.

#!/bin/bash

sbatch \
    --job-name="htseq-count-CDS" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-CDS.%A.stderr.txt" \
    --output="${err_out}-CDS.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "CDS" \
        --idattr "Parent" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-CDS.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
…with respect to type “gene” (“intron-only-filtering” call to GffRead)

Create the counts matrix by looking at parent “gene” features from the files output in section “On calling gffread above.

#!/bin/bash
sbatch \
    --job-name="htseq-count-gene" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-gene.%A.stderr.txt" \
    --output="${err_out}-gene.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "gene" \
        --idattr "ID" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-gene.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"


III. The general workflow for making the filtered gtfs

  1. Read in and process gtf/gff3 files (as dataframes)
  2. Read in and process counts matrices: “locus”, “mRNA”, “exon”, “CDS”, and “gene” (intron-only-filtering)
  3. Categorize putative transcripts/transfrags by percentile: from percentile 5 to percentile 95 in steps of 5
  4. Subset dataframes to retain percentile-filtered IDs: “locus”, “mRNA”, “exon”, “CDS”, and “gene” (intron-only-filtering)
  5. Write out processed gtfs

IV. Copying over files to Alison

#!/bin/bash

mkdir -p /home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/{gtf-gff3,tsv}
# mkdir: created directory '/home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410'
# mkdir: created directory '/home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/gtf-gff3'
# mkdir: created directory '/home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/tsv'

cd /home/kalavatt/tsukiyamalab/kalavatt/2022_transcriptome-construction/results/2023-0215

cp -r \
    outfiles_gtf-gff3/Trinity-GG \
    /home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/gtf-gff3

cp -r \
    outfiles_htseq-count/Trinity-GG \
    /home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/tsv

#  Manually copying in the 'filtered/' subdirectories from local to remote



0–2. Command-line work

See work_assessment-processing_gtfs_part-0.md, where steps 0 through 3 are detailed. Below, we pick up with step 4.

3. Perform quantile filtering of putative transcripts/transfrags

Get situated

Code

Code: Get situated

#START

#!/usr/bin/env Rscript

library(GenomicRanges)
Loading required package: stats4
Loading required package: BiocGenerics

Attaching package: ‘BiocGenerics’

The following objects are masked from ‘package:stats’:

    IQR, mad, sd, var, xtabs

The following objects are masked from ‘package:base’:

    anyDuplicated, aperm, append, as.data.frame, basename, cbind, colnames, dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank, rbind, Reduce,
    rownames, sapply, setdiff, sort, table, tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: ‘S4Vectors’

The following objects are masked from ‘package:base’:

    expand.grid, I, unname

Loading required package: IRanges
Loading required package: GenomeInfoDb
library(IRanges)
library(readxl)
library(rtracklayer)
library(tidyverse)
Registered S3 methods overwritten by 'dbplyr':
  method         from
  print.tbl_lazy     
  print.tbl_sql      
── Attaching packages ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.2 ──✔ ggplot2 3.4.2     ✔ purrr   1.0.1
✔ tibble  3.2.1     ✔ dplyr   1.1.1
✔ tidyr   1.3.0     ✔ stringr 1.5.0
✔ readr   2.1.4     ✔ forcats 1.0.0Warning: package ‘ggplot2’ was built under R version 4.2.3Warning: package ‘tibble’ was built under R version 4.2.3Warning: package ‘dplyr’ was built under R version 4.2.3── Conflicts ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::collapse()   masks IRanges::collapse()
✖ dplyr::combine()    masks BiocGenerics::combine()
✖ dplyr::desc()       masks IRanges::desc()
✖ tidyr::expand()     masks S4Vectors::expand()
✖ dplyr::filter()     masks stats::filter()
✖ dplyr::first()      masks S4Vectors::first()
✖ dplyr::lag()        masks stats::lag()
✖ ggplot2::Position() masks BiocGenerics::Position(), base::Position()
✖ purrr::reduce()     masks GenomicRanges::reduce(), IRanges::reduce()
✖ dplyr::rename()     masks S4Vectors::rename()
✖ dplyr::slice()      masks IRanges::slice()
options(scipen = 999)
options(ggrepel.max.overlaps = Inf)

if(stringr::str_detect(getwd(), "kalavattam")) {
    p_local <- "/Users/kalavattam/Dropbox/FHCC"
} else {
    p_local <- "/Users/kalavatt/projects-etc"
}
p_wd <- "2022_transcriptome-construction/results/2023-0215"

setwd(paste(p_local, p_wd, sep = "/"))
getwd()
[1] "/Users/kalavatt/projects-etc/2022_transcriptome-construction/results/2023-0215"
rm(p_local, p_wd)


Read in and process gtf files (as data.frames)

Code

Code: Read in and process gtf files (as data.frames)
#!/usr/bin/env Rscript

#  Initialize functions ---------------
import_g <- function(file) {
    rtracklayer::import(file)
}


read_in_gtfs <- function(vector_files) {
    list <- sapply(
        vector_files,
        import_g,
        simplify = FALSE,
        USE.NAMES = TRUE
    )
    names(list) <- paste0("k", c(1, 16, 2, 32, 4, 8))
    
    df <- sapply(
        list,
        as.data.frame,
        simplify = FALSE,
        USE.NAMES = TRUE
    )
    return(df)
}


#  G1 ---------------------------------
path_gtf_G <- "outfiles_gtf-gff3/Trinity-GG/G_N"
files_G <- list.files(
    path_gtf_G,
    pattern = "*.gffread.gff3",
    full.names = TRUE
)
l_G_gtf <- read_in_gtfs(files_G)

files_G_introns_filtered <- list.files(
    path_gtf_G,
    pattern = "*.gffread-intron-filtering-only.gff3",
    full.names = TRUE
)
l_G_gtf_introns_filtered <- read_in_gtfs(files_G_introns_filtered)


#  Q ----------------------------------
path_gtf_Q <- "outfiles_gtf-gff3/Trinity-GG/Q_N"
files_Q <- list.files(
    path_gtf_Q,
    pattern = "*.gffread.gff3",
    full.names = TRUE
)
l_Q_gtf <- read_in_gtfs(files_Q)

files_Q_introns_filtered <- list.files(
    path_gtf_Q,
    pattern = "*.gffread-intron-filtering-only.gff3",
    full.names = TRUE
)
l_Q_gtf_introns_filtered <- read_in_gtfs(files_Q_introns_filtered)


#  Comparisons ------------------------
# l_G_gtf[["k1"]] %>% head()
# l_G_gtf[["k2"]] %>% head()
# 
# l_G_gtf[["k1"]] %>% head()
# l_Q_gtf[["k1"]] %>% head()
# 
# l_Q_gtf[["k1"]] %>% head()
# l_Q_gtf[["k2"]] %>% head()


Read in and process counts matrices

Code

Code: Read in and process counts matrices
#!/usr/bin/env Rscript

#  Initialize functions ---------------
read_in_mat <- function(vector_of_files) {
    out_list <- sapply(
        vector_of_files,
        readr::read_tsv,
        simplify = FALSE,
        USE.NAMES = TRUE
    )
    names(out_list) <- paste0("k", c(1, 16, 2, 32, 4, 8))
    
    return(out_list)
}


rename_columns <- function(list) {
    lapply(
        list,
        function(df) {
            names(df) <- gsub("bams_renamed\\/UT_prim_UMI\\/WT_", "", names(df)) %>%
                gsub("_day1_ovn_", "_", .) %>%
                gsub("_day7_ovn_", "_", .) %>% 
                gsub("_aux-F_tc-F_", "_", .) %>%
                gsub("_tech1\\.UT_prim_UMI\\.bam", "", .) %>%
                gsub("^\\.\\.\\.1", "id", .)
            
            return(df)
        }
    )
}


#  G1 ---------------------------------
path_mat_G <- "outfiles_htseq-count/Trinity-GG/G_N"

files_G_locus <- list.files(
    path_mat_G, pattern = "*-locus.tsv", full.names = TRUE
)
l_G_mat_locus <- read_in_mat(files_G_locus) %>%
    suppressMessages()

files_G_mRNA <- list.files(
    path_mat_G, pattern = "*-mRNA.tsv", full.names = TRUE
)
l_G_mat_mRNA <- read_in_mat(files_G_mRNA) %>%
    suppressMessages()

files_G_exon <- list.files(
    path_mat_G, pattern = "*-exon.tsv", full.names = TRUE
)
l_G_mat_exon <- read_in_mat(files_G_exon) %>%
    suppressMessages()

files_G_CDS <- list.files(
    path_mat_G, pattern = "*-CDS.tsv", full.names = TRUE
)
l_G_mat_CDS <- read_in_mat(files_G_CDS) %>%
    suppressMessages()

files_G_introns_filtered <- list.files(
    path_mat_G,
    pattern = "*.gffread-intron-filtering-only.hc-strd-eq-gene.tsv",
    full.names = TRUE
)
l_G_mat_introns_filtered <- read_in_mat(files_G_introns_filtered) %>%
    suppressMessages()


#  Q ----------------------------------
path_mat_Q <- "outfiles_htseq-count/Trinity-GG/Q_N"

files_Q_locus <- list.files(
    path_mat_Q, pattern = "*-locus.tsv", full.names = TRUE
)
l_Q_mat_locus <- read_in_mat(files_Q_locus) %>%
    suppressMessages()

files_Q_mRNA <- list.files(
    path_mat_Q, pattern = "*-mRNA.tsv", full.names = TRUE
)
l_Q_mat_mRNA <- read_in_mat(files_Q_mRNA) %>%
    suppressMessages()

files_Q_exon <- list.files(
    path_mat_Q, pattern = "*-exon.tsv", full.names = TRUE
)
l_Q_mat_exon <- read_in_mat(files_Q_exon) %>%
    suppressMessages()

files_Q_CDS <- list.files(
    path_mat_Q, pattern = "*-CDS.tsv", full.names = TRUE
)
l_Q_mat_CDS <- read_in_mat(files_Q_CDS) %>%
    suppressMessages()

files_Q_introns_filtered <- list.files(
    path_mat_Q,
    pattern = "*.gffread-intron-filtering-only.hc-strd-eq-gene.tsv",
    full.names = TRUE
)
l_Q_mat_introns_filtered <- read_in_mat(files_Q_introns_filtered) %>%
    suppressMessages()


#  Comparisons ------------------------
# l_Q_mat_sam[["k1"]] %>% head()
# l_Q_mat_sam[["k2"]] %>% head()
# 
# l_Q_mat_sam[["k1"]] %>% head()
# l_Q_mat_rev[["k1"]] %>% head()


#  Rename columns ---------------------
#+ ...in each dataframe composing each list
l_G_mat_locus <- rename_columns(l_G_mat_locus)
l_G_mat_mRNA <- rename_columns(l_G_mat_mRNA)
l_G_mat_exon <- rename_columns(l_G_mat_exon)
l_G_mat_CDS <- rename_columns(l_G_mat_CDS)
l_G_mat_introns_filtered <- rename_columns(l_G_mat_introns_filtered)

l_Q_mat_locus <- rename_columns(l_Q_mat_locus)
l_Q_mat_mRNA <- rename_columns(l_Q_mat_mRNA)
l_Q_mat_exon <- rename_columns(l_Q_mat_exon)
l_Q_mat_CDS <- rename_columns(l_Q_mat_CDS)
l_Q_mat_introns_filtered <- rename_columns(l_Q_mat_introns_filtered)


Categorize putative transcripts/transcript fragments by percentile

Code

Code: Categorize putative transcripts/transcript fragments by percentile
#!/usr/bin/env Rscript

#  Initialize function ----------------
filter_transfrags <- function(x, y) {
    df <- x
    
    if(y == "G1" | y == "G") {
        df <- x[, 1:3] %>% head(., -5)
    } else if(y == "Q") {
        df <- x[, c(1, 6, 7)] %>% head(., -5)
    } else if(y != "G1" | y != "G" | y != "Q") {
        stop("Parameter y must be either 'G1', 'G', or 'Q'")
    }
    
    df[, 4] <- df[, 2] + df[, 3]
    colnames(df)[4] <- "sum"

    ids <- list()

    ids$percentiles <- quantile(
        df$sum,
        probs = c(
            0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50,
            0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95
        )
    ) %>%
        round()
    
    df$below_05 <- ifelse(df$sum <= ids$percentiles[1], TRUE, FALSE)
    df$below_10 <- ifelse(df$sum <= ids$percentiles[2], TRUE, FALSE)
    df$below_15 <- ifelse(df$sum <= ids$percentiles[3], TRUE, FALSE)
    df$below_20 <- ifelse(df$sum <= ids$percentiles[4], TRUE, FALSE)
    df$below_25 <- ifelse(df$sum <= ids$percentiles[5], TRUE, FALSE)
    df$below_30 <- ifelse(df$sum <= ids$percentiles[6], TRUE, FALSE)
    df$below_35 <- ifelse(df$sum <= ids$percentiles[7], TRUE, FALSE)
    df$below_40 <- ifelse(df$sum <= ids$percentiles[8], TRUE, FALSE)
    df$below_45 <- ifelse(df$sum <= ids$percentiles[9], TRUE, FALSE)
    df$below_50 <- ifelse(df$sum <= ids$percentiles[10], TRUE, FALSE)
    df$below_55 <- ifelse(df$sum <= ids$percentiles[11], TRUE, FALSE)
    df$below_60 <- ifelse(df$sum <= ids$percentiles[12], TRUE, FALSE)
    df$below_65 <- ifelse(df$sum <= ids$percentiles[13], TRUE, FALSE)
    df$below_70 <- ifelse(df$sum <= ids$percentiles[14], TRUE, FALSE)
    df$below_75 <- ifelse(df$sum <= ids$percentiles[15], TRUE, FALSE)
    df$below_80 <- ifelse(df$sum <= ids$percentiles[16], TRUE, FALSE)
    df$below_85 <- ifelse(df$sum <= ids$percentiles[17], TRUE, FALSE)
    df$below_90 <- ifelse(df$sum <= ids$percentiles[18], TRUE, FALSE)
    df$below_95 <- ifelse(df$sum <= ids$percentiles[19], TRUE, FALSE)
    
    ids$below_05 <- df[df$below_05 == FALSE, ]$id
    ids$below_10 <- df[df$below_10 == FALSE, ]$id
    ids$below_15 <- df[df$below_15 == FALSE, ]$id
    ids$below_20 <- df[df$below_20 == FALSE, ]$id
    ids$below_25 <- df[df$below_25 == FALSE, ]$id
    ids$below_30 <- df[df$below_30 == FALSE, ]$id
    ids$below_35 <- df[df$below_35 == FALSE, ]$id
    ids$below_40 <- df[df$below_40 == FALSE, ]$id
    ids$below_45 <- df[df$below_45 == FALSE, ]$id
    ids$below_50 <- df[df$below_50 == FALSE, ]$id
    ids$below_55 <- df[df$below_55 == FALSE, ]$id
    ids$below_60 <- df[df$below_60 == FALSE, ]$id
    ids$below_65 <- df[df$below_65 == FALSE, ]$id
    ids$below_70 <- df[df$below_70 == FALSE, ]$id
    ids$below_75 <- df[df$below_75 == FALSE, ]$id
    ids$below_80 <- df[df$below_80 == FALSE, ]$id
    ids$below_85 <- df[df$below_85 == FALSE, ]$id
    ids$below_90 <- df[df$below_90 == FALSE, ]$id
    ids$below_95 <- df[df$below_95 == FALSE, ]$id
    
    return(ids)
}


#  G1 ---------------------------------
f_G_mat_locus <- sapply(
    l_G_mat_locus,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_mRNA <- sapply(
    l_G_mat_mRNA,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_exon <- sapply(
    l_G_mat_exon,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_CDS <- sapply(
    l_G_mat_CDS,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_introns_filtered <- sapply(
    l_G_mat_introns_filtered,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)

#  Q ----------------------------------
f_Q_mat_locus <- sapply(
    l_Q_mat_locus,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_mRNA <- sapply(
    l_Q_mat_mRNA,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_exon <- sapply(
    l_Q_mat_exon,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_CDS <- sapply(
    l_Q_mat_CDS,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_introns_filtered <- sapply(
    l_Q_mat_introns_filtered,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)


Subset gtf data.frame to retain percentile-filtered gene_ids

Code

Code: Subset gtf data.frame to retain percentile-filtered gene_ids
out$k4
$below_05

$below_10

$below_15

$below_20

$below_25

$below_30

$below_35

$below_40

$below_45

$below_50

$below_55

$below_60

$below_65

$below_70

$below_75

$below_80

$below_85

$below_90

$below_95
NA


Write out processed gtfs

Code

Code: Write out processed gtfs
path_G_mRNA
[1] "outfiles_gtf-gff3/Trinity-GG/G_N/filtered/mRNA"


---
title: "work_assessment-processing_gtfs_part-1.Rmd"
author: "KA"
email: "kalavatt@fredhutch.org"
output:
    html_notebook:
        toc: yes
        toc_float: true
---
<br />
<br />

## Experiment gameplan
### Text
<details>
<summary><i>Text: Experiment gameplan</i></summary>

1. Use `GffRead` to filter `Trinity`-derived `GMAP`-aligned `gff3` files.
2. Use ~~`featureCounts`~~ `htseq-count` to perform feature counting with respect to `type`s "locus", "mRNA", "exon", and "CDS" features from "base" calls to `GffRead`, and with respect to `type` "gene" from "intron-filtering-only" calls to `GffRead`.
3. Read in resulting counts matrices and `gtf` files using custom `R` code; perform processing as necessary using a mix of `bioconductor` and `tidyverse` programs.
4. In terms of raw, non-normalized alignment-to-putative transcript/transcript fragment (transfrag) tallies, retain putative transcripts/transfrags with tallies greater than or equal to a given percentile; in this case, generate results for the 5th to 95th percentiles in iterations of five.
6. Use ~~`rtracklayer`~~ *custom code* to write the converted, collapsed, counts-filtered data objects as `gtf` files.
7. Send the processed `gtf` files to Alison Greenlaw for inspection.

For both Q and G1, Alison asked me to filter the assemblies generated with `Trinity` parameter `mkc` = 1, 4, 8. However, for the sake of completeness, and to understand clearly what "incorrectness" looks like, I will filter `mkc` = 2, 16, 32 as well. Remember that the `Trinity` parameters `mir`, `mg`, and `gf` were held at default levels for the specific assemblies to surveyed by Alison.
</details>
<br />
<br />

## Additional details
### Text, code
<details>
<summary><i>Text, code: Additional details</i></summary>

#### I. On calling `gffread`
```{bash, eval=FALSE}
#!/bin/bash

#  "Base" call to GffRead
gffread \
    -v \
    -g "${fasta_g}" \
    -i 1000 \
    -Z \
    -M -K -Q \
    -F -N -P \
    --force-exons --gene2exon \
    -o "${out}" \
    <(awk -F '\t' 'BEGIN {OFS = FS} { gsub(/chr/, "", $1); gsub(/M/, "Mito", $1); print }' "${in}") \
         > >(tee -a "${err_out%.}.stdout.txt") \
        2> >(tee -a "${err_out%.}.stderr.txt")

#  "Intron-filtering-only" call to GffRead
#+ 
#+ No collapsing, merging with these files; only filtering to exclude exonic
#+ features with introns greater than 1000 bp in length
gffread \
    -v -O \
    -i 1000 \
    -o "${out/.gff3/-intron-filtering-only.gff3}" \
    <(awk -F '\t' 'BEGIN {OFS = FS} { gsub(/chr/, "", $1); gsub(/M/, "Mito", $1); print }' "${in}") \
         > >(tee -a "${err_out%.}-intron-filtering-only.stdout.txt") \
        2> >(tee -a "${err_out%.}-intron-filtering-only.stderr.txt")
```

##### Meaning of parameters
###### "Base" call to `GffRead`
- `-v` expose (warn about) duplicate transcript IDs and other potential problems with the given GFF/GTF records
- `-g` full path to a fasta file with the genomic sequences for all input mappings (one per genomic sequence, with file names matching sequence names) (#NOTE i.e., the fasta - file output from running Trinity in genome-guided mode)
- `-i` discard transcripts having an intron larger than 1000 bp
- `-Z` merge very close exons into a single exon (when intron size<4)
- `-M` cluster the input transcripts into loci, discarding "redundant" transcripts (those with the same exact introns and fully contained or equal boundaries)
- `-K` for the -M option, also discard as redundant the shorter, fully contained transcripts (intron chains matching a part of the container)
- `-Q` for the -M option, no longer require boundary containment when assessing redundancy (can be combined with -K); only introns have to match for multi-exon transcripts, and >=80% overlap for single-exon transcripts
- `-F` keep all GFF attributes (for non-exon features)
- `-N` discard multi-exon mRNAs that have any intron with a non-canonical splice site consensus (i.e., not GT-AG, GC-AG or AT-AC)
- `-P` add transcript level GFF attributes about the coding status of each transcript, including partialness or in-frame stop codons (requires -g)
- `--force-exons` make sure that the lowest level GFF features are considered "exon" features (#NOTE This is standard in gff3 and gtf files)
- `-o` write the output records into <outfile> instead of stdout

###### "Intron-filtering-only" call to `GffRead`
- `-v` expose (warn about) duplicate transcript IDs and other potential problems with the given GFF/GTF records
- `-O` process other non-transcript GFF records (by default non-transcript records are ignored) (`#NOTE` This keeps 'gene' features (output by gmap) in the gff3/gtf, although "gene" is exactly the same as "mRNA" as output by gmap)
- `-i` discard transcripts having an intron larger than 1000 bp
- `-o` write the output records into <outfile> instead of stdout
<br />

#### II. On calling `htseq-count`
##### ...with respect to `type` "locus"
As a result of calling gffread with the `-Z` `-M` `-K` and `-Q` arguments, a new feature is added to the gff3/gtf files: "locus". "locus" is a putative parent feature made from collapsing and joining "children" features (hierarchically, "mRNA" and "exon") as described for `-Z` `-M` `-K` and `-Q`. This is an extension of the kind of collapsing performed by `gffcompare -C`. Thus, counts matrices were created with respect to these "locus" features.

```{bash, eval=FALSE}
#!/bin/bash

sbatch \
    --job-name="htseq-count-locus" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-locus.%A.stderr.txt" \
    --output="${err_out}-locus.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "locus" \
        --idattr "ID" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-locus.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
```

##### ...with respect to `type` "mRNA"
Create the counts matrix by looking at children "mRNA" features rather than parent "locus" features. This is the kind of collapsing performed by `gffcompare -C`.

```{bash, eval=FALSE}
#!/bin/bash

sbatch \
    --job-name="htseq-count-mRNA" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-mRNA.%A.stderr.txt" \
    --output="${err_out}-mRNA.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "mRNA" \
        --idattr "ID" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-mRNA.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
```

##### ...with respect to `type` "exon"
Create the counts matrix by looking at children "exon" features.

```{bash, eval=FALSE}
#!/bin/bash

sbatch \
    --job-name="htseq-count-exon" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-exon.%A.stderr.txt" \
    --output="${err_out}-exon.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "exon" \
        --idattr "Parent" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-exon.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
```

##### ...with respect to `type` "CDS"
`gffread` scans the `fasta`s supplied `-g` and roughly estimates start and stop codons from the nt sequences; it then adds these CDS estimates to the `gff3`/`gtf` files. Create the counts matrix by looking at these estimated "CDS" features.

```{bash, eval=FALSE}
#!/bin/bash

sbatch \
    --job-name="htseq-count-CDS" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-CDS.%A.stderr.txt" \
    --output="${err_out}-CDS.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "CDS" \
        --idattr "Parent" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-CDS.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
```

##### ...with respect to `type` "gene" ("intron-only-filtering" call to `GffRead`)
Create the counts matrix by looking at parent "gene" features from the files output in section <b>"On calling `gffread`"</b> above.

```{bash, eval=FALSE}
#!/bin/bash
sbatch \
    --job-name="htseq-count-gene" \
    --nodes=1 \
    --cpus-per-task=8 \
    --error="${err_out}-gene.%A.stderr.txt" \
    --output="${err_out}-gene.%A.stdout.txt" \
    htseq-count \
        --order "pos" \
        --stranded "${hc_strd}" \
        --nonunique "all" \
        --type "gene" \
        --idattr "ID" \
        --nprocesses 8 \
        --counts_output "${out/.tsv/-gene.tsv}" \
        --with-header \
        ${bams[*]} \
        "${in}"
```
<br />

#### III. The general workflow for making the filtered gtfs
1. Read in and process `gtf`/`gff3` files (as dataframes)
2. Read in and process counts matrices: "locus", "mRNA", "exon", "CDS", and "gene" (intron-only-filtering)
3. Categorize putative transcripts/transfrags by percentile: from percentile 5 to percentile 95 in steps of 5
4. Subset dataframes to retain percentile-filtered IDs: "locus", "mRNA", "exon", "CDS", and "gene" (intron-only-filtering)
5. Write out processed `gtf`s
<br />

#### IV. Copying over files to Alison
```{bash, eval=FALSE}
#!/bin/bash

mkdir -p /home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/{gtf-gff3,tsv}
# mkdir: created directory '/home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410'
# mkdir: created directory '/home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/gtf-gff3'
# mkdir: created directory '/home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/tsv'

cd /home/kalavatt/tsukiyamalab/kalavatt/2022_transcriptome-construction/results/2023-0215

cp -r \
    outfiles_gtf-gff3/Trinity-GG \
    /home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/gtf-gff3

cp -r \
    outfiles_htseq-count/Trinity-GG \
    /home/kalavatt/tsukiyamalab/alisong/KA.gtfs_quantile-filtered_Trinity-GG_G1-Q_2023-0410/tsv

#  Manually copying in the 'filtered/' subdirectories from local to remote
```
</details>
<br />
<br />

## 0&ndash;2. Command-line work
See [`work_assessment-processing_gtfs_part-0.md`](./work_assessment-processing_gtfs_part-0.md), where *steps 0 through 3* are detailed. Below, we pick up with *step 4*.
<br />
<br />

## 3. Perform quantile filtering of putative transcripts/transfrags
### Get situated
#### Code
<details>
<summary><i>Code: Get situated</i></summary>

`#START`
```{r}
#!/usr/bin/env Rscript

library(GenomicRanges)
library(IRanges)
library(readxl)
library(rtracklayer)
library(tidyverse)

options(scipen = 999)
options(ggrepel.max.overlaps = Inf)

if(stringr::str_detect(getwd(), "kalavattam")) {
    p_local <- "/Users/kalavattam/Dropbox/FHCC"
} else {
    p_local <- "/Users/kalavatt/projects-etc"
}
p_wd <- "2022_transcriptome-construction/results/2023-0215"

setwd(paste(p_local, p_wd, sep = "/"))
getwd()

rm(p_local, p_wd)
```
</details>
<br />

### Read in and process `gtf` files (as `data.frame`s)
#### Code
<details>
<summary><i>Code: Read in and process `gtf` files (as `data.frame`s)</i></summary>

```{r}
#!/usr/bin/env Rscript

#  Initialize functions ---------------
import_g <- function(file) {
    rtracklayer::import(file)
}


read_in_gtfs <- function(vector_files) {
    list <- sapply(
        vector_files,
        import_g,
        simplify = FALSE,
        USE.NAMES = TRUE
    )
    names(list) <- paste0("k", c(1, 16, 2, 32, 4, 8))
    
    df <- sapply(
        list,
        as.data.frame,
        simplify = FALSE,
        USE.NAMES = TRUE
    )
    return(df)
}


#  G1 ---------------------------------
path_gtf_G <- "outfiles_gtf-gff3/Trinity-GG/G_N"
files_G <- list.files(
    path_gtf_G,
    pattern = "*.gffread.gff3",
    full.names = TRUE
)
l_G_gtf <- read_in_gtfs(files_G)

files_G_introns_filtered <- list.files(
    path_gtf_G,
    pattern = "*.gffread-intron-filtering-only.gff3",
    full.names = TRUE
)
l_G_gtf_introns_filtered <- read_in_gtfs(files_G_introns_filtered)


#  Q ----------------------------------
path_gtf_Q <- "outfiles_gtf-gff3/Trinity-GG/Q_N"
files_Q <- list.files(
    path_gtf_Q,
    pattern = "*.gffread.gff3",
    full.names = TRUE
)
l_Q_gtf <- read_in_gtfs(files_Q)

files_Q_introns_filtered <- list.files(
    path_gtf_Q,
    pattern = "*.gffread-intron-filtering-only.gff3",
    full.names = TRUE
)
l_Q_gtf_introns_filtered <- read_in_gtfs(files_Q_introns_filtered)


#  Comparisons ------------------------
# l_G_gtf[["k1"]] %>% head()
# l_G_gtf[["k2"]] %>% head()
# 
# l_G_gtf[["k1"]] %>% head()
# l_Q_gtf[["k1"]] %>% head()
# 
# l_Q_gtf[["k1"]] %>% head()
# l_Q_gtf[["k2"]] %>% head()
```
</details>
<br />

### Read in and process counts matrices
#### Code
<details>
<summary><i>Code: Read in and process counts matrices</i></summary>

```{r}
#!/usr/bin/env Rscript

#  Initialize functions ---------------
read_in_mat <- function(vector_of_files) {
    out_list <- sapply(
        vector_of_files,
        readr::read_tsv,
        simplify = FALSE,
        USE.NAMES = TRUE
    )
    names(out_list) <- paste0("k", c(1, 16, 2, 32, 4, 8))
    
    return(out_list)
}


rename_columns <- function(list) {
    lapply(
        list,
        function(df) {
            names(df) <- gsub("bams_renamed\\/UT_prim_UMI\\/WT_", "", names(df)) %>%
                gsub("_day1_ovn_", "_", .) %>%
                gsub("_day7_ovn_", "_", .) %>% 
                gsub("_aux-F_tc-F_", "_", .) %>%
                gsub("_tech1\\.UT_prim_UMI\\.bam", "", .) %>%
                gsub("^\\.\\.\\.1", "id", .)
            
            return(df)
        }
    )
}


#  G1 ---------------------------------
path_mat_G <- "outfiles_htseq-count/Trinity-GG/G_N"

files_G_locus <- list.files(
    path_mat_G, pattern = "*-locus.tsv", full.names = TRUE
)
l_G_mat_locus <- read_in_mat(files_G_locus) %>%
    suppressMessages()

files_G_mRNA <- list.files(
    path_mat_G, pattern = "*-mRNA.tsv", full.names = TRUE
)
l_G_mat_mRNA <- read_in_mat(files_G_mRNA) %>%
    suppressMessages()

files_G_exon <- list.files(
    path_mat_G, pattern = "*-exon.tsv", full.names = TRUE
)
l_G_mat_exon <- read_in_mat(files_G_exon) %>%
    suppressMessages()

files_G_CDS <- list.files(
    path_mat_G, pattern = "*-CDS.tsv", full.names = TRUE
)
l_G_mat_CDS <- read_in_mat(files_G_CDS) %>%
    suppressMessages()

files_G_introns_filtered <- list.files(
    path_mat_G,
    pattern = "*.gffread-intron-filtering-only.hc-strd-eq-gene.tsv",
    full.names = TRUE
)
l_G_mat_introns_filtered <- read_in_mat(files_G_introns_filtered) %>%
    suppressMessages()


#  Q ----------------------------------
path_mat_Q <- "outfiles_htseq-count/Trinity-GG/Q_N"

files_Q_locus <- list.files(
    path_mat_Q, pattern = "*-locus.tsv", full.names = TRUE
)
l_Q_mat_locus <- read_in_mat(files_Q_locus) %>%
    suppressMessages()

files_Q_mRNA <- list.files(
    path_mat_Q, pattern = "*-mRNA.tsv", full.names = TRUE
)
l_Q_mat_mRNA <- read_in_mat(files_Q_mRNA) %>%
    suppressMessages()

files_Q_exon <- list.files(
    path_mat_Q, pattern = "*-exon.tsv", full.names = TRUE
)
l_Q_mat_exon <- read_in_mat(files_Q_exon) %>%
    suppressMessages()

files_Q_CDS <- list.files(
    path_mat_Q, pattern = "*-CDS.tsv", full.names = TRUE
)
l_Q_mat_CDS <- read_in_mat(files_Q_CDS) %>%
    suppressMessages()

files_Q_introns_filtered <- list.files(
    path_mat_Q,
    pattern = "*.gffread-intron-filtering-only.hc-strd-eq-gene.tsv",
    full.names = TRUE
)
l_Q_mat_introns_filtered <- read_in_mat(files_Q_introns_filtered) %>%
    suppressMessages()


#  Comparisons ------------------------
# l_Q_mat_sam[["k1"]] %>% head()
# l_Q_mat_sam[["k2"]] %>% head()
# 
# l_Q_mat_sam[["k1"]] %>% head()
# l_Q_mat_rev[["k1"]] %>% head()


#  Rename columns ---------------------
#+ ...in each dataframe composing each list
l_G_mat_locus <- rename_columns(l_G_mat_locus)
l_G_mat_mRNA <- rename_columns(l_G_mat_mRNA)
l_G_mat_exon <- rename_columns(l_G_mat_exon)
l_G_mat_CDS <- rename_columns(l_G_mat_CDS)
l_G_mat_introns_filtered <- rename_columns(l_G_mat_introns_filtered)

l_Q_mat_locus <- rename_columns(l_Q_mat_locus)
l_Q_mat_mRNA <- rename_columns(l_Q_mat_mRNA)
l_Q_mat_exon <- rename_columns(l_Q_mat_exon)
l_Q_mat_CDS <- rename_columns(l_Q_mat_CDS)
l_Q_mat_introns_filtered <- rename_columns(l_Q_mat_introns_filtered)
```
</details>
<br />

### Categorize putative transcripts/transcript fragments by percentile
#### Code
<details>
<summary><i>Code: Categorize putative transcripts/transcript fragments by percentile</i></summary>

```{r}
#!/usr/bin/env Rscript

#  Initialize function ----------------
filter_transfrags <- function(x, y) {
    df <- x
    
    if(y == "G1" | y == "G") {
        df <- x[, 1:3] %>% head(., -5)
    } else if(y == "Q") {
        df <- x[, c(1, 6, 7)] %>% head(., -5)
    } else if(y != "G1" | y != "G" | y != "Q") {
        stop("Parameter y must be either 'G1', 'G', or 'Q'")
    }
    
    df[, 4] <- df[, 2] + df[, 3]
    colnames(df)[4] <- "sum"

    ids <- list()

    ids$percentiles <- quantile(
        df$sum,
        probs = c(
            0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50,
            0.55, 0.60, 0.65, 0.70, 0.75, 0.80, 0.85, 0.90, 0.95
        )
    ) %>%
        round()
    
    df$below_05 <- ifelse(df$sum <= ids$percentiles[1], TRUE, FALSE)
    df$below_10 <- ifelse(df$sum <= ids$percentiles[2], TRUE, FALSE)
    df$below_15 <- ifelse(df$sum <= ids$percentiles[3], TRUE, FALSE)
    df$below_20 <- ifelse(df$sum <= ids$percentiles[4], TRUE, FALSE)
    df$below_25 <- ifelse(df$sum <= ids$percentiles[5], TRUE, FALSE)
    df$below_30 <- ifelse(df$sum <= ids$percentiles[6], TRUE, FALSE)
    df$below_35 <- ifelse(df$sum <= ids$percentiles[7], TRUE, FALSE)
    df$below_40 <- ifelse(df$sum <= ids$percentiles[8], TRUE, FALSE)
    df$below_45 <- ifelse(df$sum <= ids$percentiles[9], TRUE, FALSE)
    df$below_50 <- ifelse(df$sum <= ids$percentiles[10], TRUE, FALSE)
    df$below_55 <- ifelse(df$sum <= ids$percentiles[11], TRUE, FALSE)
    df$below_60 <- ifelse(df$sum <= ids$percentiles[12], TRUE, FALSE)
    df$below_65 <- ifelse(df$sum <= ids$percentiles[13], TRUE, FALSE)
    df$below_70 <- ifelse(df$sum <= ids$percentiles[14], TRUE, FALSE)
    df$below_75 <- ifelse(df$sum <= ids$percentiles[15], TRUE, FALSE)
    df$below_80 <- ifelse(df$sum <= ids$percentiles[16], TRUE, FALSE)
    df$below_85 <- ifelse(df$sum <= ids$percentiles[17], TRUE, FALSE)
    df$below_90 <- ifelse(df$sum <= ids$percentiles[18], TRUE, FALSE)
    df$below_95 <- ifelse(df$sum <= ids$percentiles[19], TRUE, FALSE)
    
    ids$below_05 <- df[df$below_05 == FALSE, ]$id
    ids$below_10 <- df[df$below_10 == FALSE, ]$id
    ids$below_15 <- df[df$below_15 == FALSE, ]$id
    ids$below_20 <- df[df$below_20 == FALSE, ]$id
    ids$below_25 <- df[df$below_25 == FALSE, ]$id
    ids$below_30 <- df[df$below_30 == FALSE, ]$id
    ids$below_35 <- df[df$below_35 == FALSE, ]$id
    ids$below_40 <- df[df$below_40 == FALSE, ]$id
    ids$below_45 <- df[df$below_45 == FALSE, ]$id
    ids$below_50 <- df[df$below_50 == FALSE, ]$id
    ids$below_55 <- df[df$below_55 == FALSE, ]$id
    ids$below_60 <- df[df$below_60 == FALSE, ]$id
    ids$below_65 <- df[df$below_65 == FALSE, ]$id
    ids$below_70 <- df[df$below_70 == FALSE, ]$id
    ids$below_75 <- df[df$below_75 == FALSE, ]$id
    ids$below_80 <- df[df$below_80 == FALSE, ]$id
    ids$below_85 <- df[df$below_85 == FALSE, ]$id
    ids$below_90 <- df[df$below_90 == FALSE, ]$id
    ids$below_95 <- df[df$below_95 == FALSE, ]$id
    
    return(ids)
}


#  G1 ---------------------------------
f_G_mat_locus <- sapply(
    l_G_mat_locus,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_mRNA <- sapply(
    l_G_mat_mRNA,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_exon <- sapply(
    l_G_mat_exon,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_CDS <- sapply(
    l_G_mat_CDS,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)
f_G_mat_introns_filtered <- sapply(
    l_G_mat_introns_filtered,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "G1"
)

#  Q ----------------------------------
f_Q_mat_locus <- sapply(
    l_Q_mat_locus,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_mRNA <- sapply(
    l_Q_mat_mRNA,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_exon <- sapply(
    l_Q_mat_exon,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_CDS <- sapply(
    l_Q_mat_CDS,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
f_Q_mat_introns_filtered <- sapply(
    l_Q_mat_introns_filtered,
    filter_transfrags,
    simplify = FALSE,
    USE.NAMES = TRUE,
    y = "Q"
)
```
</details>
<br />

### Subset `gtf` `data.frame` to retain percentile-filtered `gene_id`s
#### Code
<details>
<summary><i>Code: Subset `gtf` `data.frame` to retain percentile-filtered `gene_id`s</i></summary>

```{r}
#!/usr/bin/env Rscript

#  Initialize functions ---------------
flatten_elements_to_one <- function(x) {
    # For character list elements with two or more subelements, collapse
    # ("flatten") the subelements into a single character element
    # 
    # :param x: <list>
    # :return: character vector of collapsed list elements (list e)
    l_collapsed <- x[lengths(x) >= 2] %>% length()
    collapsed <- vector(mode = "character", length = l_collapsed)
    for(i in 1:l_collapsed) {
        # i <- 1
        # cat(i, "\n")
        # cat(x[lengths(x) >= 2][[i]], "\n")
        collapsed[i] <- stringr::str_c(
            x[lengths(x) >= 2][[i]],
            collapse = ", "
        )
    }
    
    return(collapsed)
}


process_list_column <- function(x) {
    # ...
    # 
    # :param x: <list>
    # :return: ...
    x[lengths(x) == 0] <- NA_character_
    if(length(x[lengths(x) >= 2]) != 0) {
        x[lengths(x) >= 2] <- x[lengths(x) >= 2] %>%
            flatten_elements_to_one()
    }
    y <- x %>% unlist()
    return(y)
}


subset_dataframes <- function(x, y, z) {
    # ...
    # 
    # :param x: list of *.gff3 files <list>
    # :param y: list of putative transcripts categorized by percentile <list>
    # :param z: feature type to examine; must be "locus", "mRNA", "exon", "CDS", or "gene" <chr>
    
    #  Tests
    # x <- l_Q_gtf
    # y <- f_Q_mat_CDS
    # z <- "CDS"
    # 
    # x <- l_G_gtf_introns_filtered
    # y <- f_G_mat_introns_filtered
    # z <- "gene"
    # 
    # x <- l_Q_gtf
    # y <- f_Q_mat_exon
    # z <- "exon"
    
    if((base::isFALSE(stringr::str_detect(z, "locus|mRNA|exon|CDS|gene")))) {
        stop("z must be \"locus\", \"mRNA\", \"exon\", \"CDS\", or \"gene\"")
    }
    
    df <- list()
    mat <- list()
    out <- list()
    
    for(i in names(x)) {
        #  Tests
        # i <- "k1"
        # i <- "k4"
        
        mat[[i]] <- y[[i]]
        
        if(base::isTRUE(z == "locus")) {
            df[[i]] <- x[[i]][x[[i]]["type"] == "locus", ]
        } else if(base::isTRUE(z == "mRNA")) {
            df[[i]] <- x[[i]][x[[i]]["type"] == "mRNA", ]
        } else if(base::isTRUE(z == "exon")) {
            df[[i]] <- x[[i]][x[[i]]["type"] == "exon", ]
        } else if(base::isTRUE(z == "CDS")) {
            df[[i]] <- x[[i]][x[[i]]["type"] == "CDS", ]
        } else if(base::isTRUE(z == "gene")) {
            df[[i]] <- x[[i]][x[[i]]["type"] == "gene", ]
        } 
        
        if(base::isTRUE(stringr::str_detect(z, "locus|mRNA|gene"))) {
            out[[i]]$below_05 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_05, ]
            out[[i]]$below_10 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_10, ]
            out[[i]]$below_15 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_15, ]
            out[[i]]$below_20 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_20, ]
            out[[i]]$below_25 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_25, ]
            out[[i]]$below_30 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_30, ]
            out[[i]]$below_35 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_35, ]
            out[[i]]$below_40 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_40, ]
            out[[i]]$below_45 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_45, ]
            out[[i]]$below_50 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_50, ]
            out[[i]]$below_55 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_55, ]
            out[[i]]$below_60 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_60, ]
            out[[i]]$below_65 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_65, ]
            out[[i]]$below_70 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_70, ]
            out[[i]]$below_75 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_75, ]
            out[[i]]$below_80 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_80, ]
            out[[i]]$below_85 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_85, ]
            out[[i]]$below_90 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_90, ]
            out[[i]]$below_95 <- df[[i]][df[[i]]$ID %in% mat[[i]]$below_95, ]
        } else if(base::isTRUE(stringr::str_detect(z, "exon|CDS"))) {
            out[[i]]$below_05 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_05, 
            ]
            out[[i]]$below_10 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_10, 
            ]
            out[[i]]$below_15 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_15, 
            ]
            out[[i]]$below_20 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_20, 
            ]
            out[[i]]$below_25 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_25, 
            ]
            out[[i]]$below_30 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_30, 
            ]
            out[[i]]$below_35 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_35, 
            ]
            out[[i]]$below_40 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_40, 
            ]
            out[[i]]$below_45 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_45, 
            ]
            out[[i]]$below_50 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_50, 
            ]
            out[[i]]$below_55 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_55, 
            ]
            out[[i]]$below_60 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_60, 
            ]
            out[[i]]$below_65 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_65, 
            ]
            out[[i]]$below_70 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_70, 
            ]
            out[[i]]$below_75 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_75, 
            ]
            out[[i]]$below_80 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_80, 
            ]
            out[[i]]$below_85 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_85, 
            ]
            out[[i]]$below_90 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_90, 
            ]
            out[[i]]$below_95 <- df[[i]][
                process_list_column(df[[i]]$Parent) %in% mat[[i]]$below_95, 
            ]
        }
    }
    
    return(out)
}


#  G1 ---------------------------------
out_G_gtf_locus <- subset_dataframes(l_G_gtf, f_G_mat_locus, "locus")
out_G_gtf_mRNA <- subset_dataframes(l_G_gtf, f_G_mat_mRNA, "mRNA")
out_G_gtf_exon <- subset_dataframes(l_G_gtf, f_G_mat_exon, "exon")
out_G_gtf_CDS <- subset_dataframes(l_G_gtf, f_G_mat_CDS, "CDS")
out_G_gtf_introns_filtered <- subset_dataframes(
    l_G_gtf_introns_filtered, f_G_mat_introns_filtered, "gene"
)


#  Q ----------------------------------
out_Q_gtf_locus <- subset_dataframes(l_Q_gtf, f_Q_mat_locus, "locus")
out_Q_gtf_mRNA <- subset_dataframes(l_Q_gtf, f_Q_mat_mRNA, "mRNA")
out_Q_gtf_exon <- subset_dataframes(l_Q_gtf, f_Q_mat_exon, "exon")
out_Q_gtf_CDS <- subset_dataframes(l_Q_gtf, f_Q_mat_CDS, "CDS")
out_Q_gtf_introns_filtered <- subset_dataframes(
    l_Q_gtf_introns_filtered, f_Q_mat_introns_filtered, "gene"
)
```
</details>
<br />

### Write out processed `gtf`s
#### Code
<details>
<summary><i>Code: Write out processed `gtf`s</i></summary>

```{r}
#!/usr/bin/env Rscript

#  Initialize functions -------------------------------------------------------
write_gtf <- function(x, y) {
    # ...
    # 
    # :param x: tibble <tibble, data.frame>
    # :param y: outfile <chr>
    # :return: NA
    readr::write_tsv(
        x,
        y,
        col_names = FALSE,
        quote = "none",
        escape = "none"
    )
}


#  Create outdirectories ------------------------------------------------------
#  G1 ---------------------------------
path_G_locus <- "outfiles_gtf-gff3/Trinity-GG/G_N/filtered/locus"
if(base::isFALSE(dir.exists(path_G_locus))) dir.create(path_G_locus, recursive = TRUE)

path_G_mRNA <- "outfiles_gtf-gff3/Trinity-GG/G_N/filtered/mRNA"
if(base::isFALSE(dir.exists(path_G_mRNA))) dir.create(path_G_mRNA, recursive = TRUE)

path_G_exon <- "outfiles_gtf-gff3/Trinity-GG/G_N/filtered/exon"
if(base::isFALSE(dir.exists(path_G_exon))) dir.create(path_G_exon, recursive = TRUE)

path_G_CDS <- "outfiles_gtf-gff3/Trinity-GG/G_N/filtered/CDS"
if(base::isFALSE(dir.exists(path_G_CDS))) dir.create(path_G_CDS, recursive = TRUE)

path_G_introns_filtered <- "outfiles_gtf-gff3/Trinity-GG/G_N/filtered/introns_filtered"
if(base::isFALSE(dir.exists(path_G_introns_filtered))) dir.create(path_G_introns_filtered, recursive = TRUE)

#  Q ----------------------------------
path_Q_locus <- "outfiles_gtf-gff3/Trinity-GG/Q_N/filtered/locus"
if(base::isFALSE(dir.exists(path_Q_locus))) dir.create(path_Q_locus, recursive = TRUE)

path_Q_mRNA <- "outfiles_gtf-gff3/Trinity-GG/Q_N/filtered/mRNA"
if(base::isFALSE(dir.exists(path_Q_mRNA))) dir.create(path_Q_mRNA, recursive = TRUE)

path_Q_exon <- "outfiles_gtf-gff3/Trinity-GG/Q_N/filtered/exon"
if(base::isFALSE(dir.exists(path_Q_exon))) dir.create(path_Q_exon, recursive = TRUE)

path_Q_CDS <- "outfiles_gtf-gff3/Trinity-GG/Q_N/filtered/CDS"
if(base::isFALSE(dir.exists(path_Q_CDS))) dir.create(path_Q_CDS, recursive = TRUE)

path_Q_introns_filtered <- "outfiles_gtf-gff3/Trinity-GG/Q_N/filtered/introns_filtered"
if(base::isFALSE(dir.exists(path_Q_introns_filtered))) dir.create(path_Q_introns_filtered, recursive = TRUE)


#  Create outdirectories ------------------------------------------------------
for(i in names(out_G_gtf_locus)) {
    for(j in c(paste0(
        "below_",
        c(
            "05", "10", "15", "20", "25", "30", "35", "40", "45", "50",
            "55", "60", "65", "70", "75", "80", "85", "90", "95"
        )
    ))) {
        for(k in c(
            path_G_locus, path_G_mRNA, path_G_exon, path_G_CDS,
            path_G_introns_filtered,
            path_Q_locus, path_Q_mRNA, path_Q_exon, path_Q_CDS,
            path_Q_introns_filtered
        )) {
            # i <- "k2"
            # j <- "below_05"
            # k <- path_Q_locus
            if(base::isTRUE(k == path_G_locus)) {
                #PICKUPHERE
                outfile <- paste0(
                    path_G_locus, "/G1_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving G1", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_G_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_G_gtf_locus[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_G_gtf_locus[[i]][[j]],
                #     paste0(
                #         path_G_locus, "/G1_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_G_mRNA)) {
                outfile <- paste0(
                    path_G_mRNA, "/G1_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving G1", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_G_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_G_gtf_mRNA[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_G_gtf_mRNA[[i]][[j]],
                #     paste0(
                #         path_G_mRNA, "/G1_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_G_exon)) {
                outfile <- paste0(
                    path_G_exon, "/G1_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving G1", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_G_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_G_gtf_exon[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_G_gtf_exon[[i]][[j]],
                #     paste0(
                #         path_G_exon, "/G1_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_G_CDS)) {
                outfile <- paste0(
                    path_G_CDS, "/G1_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving G1", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_G_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_G_gtf_CDS[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_G_gtf_CDS[[i]][[j]],
                #     paste0(
                #         path_G_CDS, "/G1_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_G_introns_filtered)) {
                outfile <- paste0(
                    path_G_introns_filtered, "/G1_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving G1", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_G_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_G_gtf_introns_filtered[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_G_gtf_introns_filtered[[i]][[j]],
                #     paste0(
                #         path_G_introns_filtered, "/G1_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_Q_locus)) {
                outfile <- paste0(
                    path_Q_locus, "/Q_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving Q", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_Q_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_Q_gtf_locus[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_Q_gtf_locus[[i]][[j]],
                #     paste0(
                #         path_Q_locus, "/Q_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_Q_mRNA)) {
                outfile <- paste0(
                    path_Q_mRNA, "/Q_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving Q", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_Q_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_Q_gtf_mRNA[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_Q_gtf_mRNA[[i]][[j]],
                #     paste0(
                #         path_Q_mRNA, "/Q_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_Q_exon)) {
                outfile <- paste0(
                    path_Q_exon, "/Q_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving Q", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_Q_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_Q_gtf_exon[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_Q_gtf_exon[[i]][[j]],
                #     paste0(
                #         path_Q_exon, "/Q_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_Q_CDS)) {
                outfile <- paste0(
                    path_Q_CDS, "/Q_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving Q", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_Q_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_Q_gtf_CDS[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_Q_gtf_CDS[[i]][[j]],
                #     paste0(
                #         path_Q_CDS, "/Q_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            } else if(base::isTRUE(k == path_Q_introns_filtered)) {
                outfile <- paste0(
                    path_Q_introns_filtered, "/Q_mkc-", gsub("k", "", i), "_",
                    gsub("below_", "gte-pctl-", j), ".gtf"
                )
                
                cat("Saving Q", i, j, "in", k, "\n")
                cat(paste0(outfile, "\n"))
                cat("\n\n")
                
                # out_Q_conv <- GenomicRanges::makeGRangesFromDataFrame(
                #     out_Q_gtf_introns_filtered[[i]][[j]], keep.extra.columns = TRUE
                # )
                # 
                # rtracklayer::export(
                #     out_Q_gtf_introns_filtered[[i]][[j]],
                #     paste0(
                #         path_Q_introns_filtered, "/Q_mkc-", gsub("k", "", i), "_",
                #         gsub("below_", "gte-pctl-", j), ".gtf"
                #     )
                # )
            }
        }
    }
}
```
</details>
<br />
